Sentence examples for mathematics understanding from inspiring English sources

The BSDT is a 24-item free-response test on basic mathematics understanding.

Several studies (Christmann et al. 1997; Clark, 1994; Povey & Ransom, 2000) found that using computers purely as a method of instruction does not improve students' mathematics understanding.

The battery used in this study included items from three components of mathematics: 'Understanding Number', 'Computation and Knowledge' and 'Non-Numerical Processes' (Kovas et al. 2007c).

The battery used in this study included questions from three components of mathematics: 'Understanding Number', 'Computation and Knowledge' and 'Non-Numerical Processes' (Kovas et al. 2007c) (see Supporting Information for a more detailed description).

Across the domains of manipulatives and whole body movements, most of the work in mathematics understanding has been conducted with younger children and, therefore, it is unclear what effects can be expected with an older population, such as college students, who are learning more sophisticated mathematics.

Assessment of mathematics targeted three components of mathematics: Understanding Number, Non-numerical Processes, and Computation and Knowledge.

Ultimately, the so-called problem of the application of mathematics—of understanding how it is possible that mathematics can be successfully applied to the physical world should—is an artificially designed issue rather than a genuine problem.

Valiant has applied methods from computer science and mathematics to understanding the human brain.

The Albertist textbook tradition of natural philosophy placed a high value on mathematics for understanding the physical world (Hoenen 1993: 328 330).

In this special issue, we have invited seven of the main contributors to this event to expand on their presentations and highlight the use of mathematics in understanding the dynamics of neural systems.

In this review we present a set of mathematical tools that are suitable for addressing the dynamics of oscillatory neural networks, broadening from a standard phase oscillator perspective to provide a practical framework for further successful applications of mathematics to understanding network dynamics in neuroscience.